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Speaker 3: It's the bunny that you swear you saw on the lawn,
Speaker 3: even if no one else believes you. Ali ward and
Speaker 3: here's ologies Hey, am I a real person? Unfortunately? I
Speaker 3: am am I intelligent. That's up for debate. But this
Speaker 3: week we are taking a dive into artificial intelligence and
Speaker 3: brain data with a scholar in the matter. So listen.
Speaker 3: The past few months been a little surreal photoshops out there,
Speaker 3: generating backgrounds to cut your cousin's ex girlfriend out of
Speaker 3: your wedding photos, chat gpt is, writing obituaries and friendly
Speaker 3: a lot of horse bucky. There's also groundbreaking labor strikes
Speaker 3: and the arts, which we covered in the field trip
Speaker 3: episode from the WGA strike lines. If you haven't heard it,
Speaker 3: I'll link in the show notes. But I heard about
Speaker 3: this guest's work and I said, please, please, please talk
Speaker 3: to me about how to feel about AI. Are we
Speaker 3: farting around the portal to a new and potentially shittier
Speaker 3: way of living? Or will AI say hey, dipshits. I
Speaker 3: ran some simulations and here's what we have to do
Speaker 3: to unextinct you in the next century. We're going to
Speaker 3: find out. So this guest has studied law Dartmouth, Harvard,
Speaker 3: and Duke, and been a professor at Vanderbilt University and
Speaker 3: is now at Duke's Institute for Genome Sciences and Policy.
Speaker 3: She recently delivered a TED talk called Your Right to
Speaker 3: Mental Privacy and the Age of Brain Sensing Tech, and
Speaker 3: just authored a new book called The Battle for Your Brain,
Speaker 3: defending the right to think freely in the age of neurotechnology.
Speaker 3: But before we chat with her, a quick thank you
Speaker 3: to patrons of the show who support at patreon dot
Speaker 3: com slash ologies for a book or more a month
Speaker 3: and submit their questions for the second half. And thank
Speaker 3: you to everyone in ologies merch dot com, shirts and
Speaker 3: hats and such. Of course, you can also support the
Speaker 3: show just by leaving a review and I may delight
Speaker 3: you by reading it, such as this one left this
Speaker 3: week by environmental lawyer Harrison Harrison Harrison, who wrote a
Speaker 3: review calling Ologies and OUI guy ratituey rip Rarin good time.
Speaker 3: So yeah, I read them all. Thank you Harrison for that. Okay,
Speaker 3: neurotechnology get into this how the brain interacts with technology
Speaker 3: and also techno neurology, how tech is striving to replicate
Speaker 3: and surpass human intelligence and what that means for us all.
Speaker 3: So let's beat up our way into a talk about texting, scrolling, cheating,
Speaker 3: brain implants, mental health, doomsday scenarios, congressional hearings, apocalypse, potential
Speaker 3: medical advances, biometric mining, and why suddenly artificial intelligence is
Speaker 3: on our minds. With law professor and neurotechnologist, doctor Nita Farhani.
Speaker 4: Nita Fahani, she her.
Speaker 3: So good to meet you, terrifying to meet you. Are
Speaker 3: you the scariest person at a dinner party because of
Speaker 3: how much you know?
Speaker 4: I'm not. I'm not a scary person, and I find
Speaker 4: that people think that it's equal parts fascinating and terrifying.
Speaker 4: So if anything, I think I'm a great dinner gas right,
Speaker 4: because they're fascinated.
Speaker 3: I definitely should clarify that you are. There's nothing scary
Speaker 3: about you. The information that you hold is like, no,
Speaker 3: I know, do I want to look? Do I not
Speaker 3: want to look? Do I want to look? It's thrilling
Speaker 3: like a horror film.
Speaker 4: Yeah, it's like people can't look away. Yeah, right, And
Speaker 4: that's good because I don't want them to look away.
Speaker 4: I want them to know. But at the same time,
Speaker 4: what I usually get is like, wait, this is real,
Speaker 4: Like what you're talking about is it actually exists? And
Speaker 4: people are really using it and employers are really using
Speaker 4: it and governments are really using it and wait what Yeah?
Speaker 3: Do you spend a lot of your time chatting with
Speaker 3: people trying to warn them or calm them down?
Speaker 4: Yes? So On the one hand, I am trying to
Speaker 4: raise the alarm and to help people understand that this
Speaker 4: whole area of being able to decode mood and really
Speaker 4: hack and track the brain is a new frontier and
Speaker 4: the final frontier of what it means to be human
Speaker 4: and privacy and freedom. And at the same time, I
Speaker 4: don't want to make people have the reactionary approach to technology,
Speaker 4: which is like, Okay, then let's banmon, because the promise
Speaker 4: is also extraordinary, and so I am very much equal
Speaker 4: part like, let me help you understand not only what
Speaker 4: the promise is and why you're likely to adopt it,
Speaker 4: but why before you do so, and before we as
Speaker 4: a society at scale adopt this technology, that we make
Speaker 4: some really important choices that'll actually make it good for
Speaker 4: us and not the most Orwellian, frightening, scary thing possible.
Speaker 3: I feel like there's few topics that have this much
Speaker 3: true ambivalence, of so much good and so much potential
Speaker 3: for misuse. Did your brain become a lawyer brain because
Speaker 3: of those sort of like philosophical conundrums. What drew you
Speaker 3: to this kind of deep deep thought?
Speaker 4: Yeah, I've always been driven to the questions that are
Speaker 4: at the intersection of philosophy and science. Like in high school,
Speaker 4: I was really interested in the science, but I was
Speaker 4: a policy debater. In college, I was government minor and
Speaker 4: science major, and I did in lab stuff, but largely
Speaker 4: things that were policy.
Speaker 3: So Nita got several graduate degrees studying law in science,
Speaker 3: behavioral genetics and neuroscience, the philosophy of mind, neuroethics, bioethics,
Speaker 3: and even reproductive rights and policy in Kenya. And she
Speaker 3: said all her work seems to gravitate towards this intersection
Speaker 3: of philosophy and law and science because she had fundamental
Speaker 3: questions like do.
Speaker 4: We have free will? And you know, do we have
Speaker 4: like fundamental autonomy and freedom and how do we put
Speaker 4: into place the protections. But I've always been fascinated and
Speaker 4: really interested in the science and the technology itself. I've
Speaker 4: never been a luttite. I've always been somebody who's an
Speaker 4: early tech adopter but clearly see what the downsides are.
Speaker 3: At the same time, where was tech at when you
Speaker 3: were getting that roster of graduate degree? Where were we at?
Speaker 3: Were we at emails? Were we at video calls?
Speaker 4: Yeah? So we were not at video calls. We were
Speaker 4: at emails. The Internet existed, we used it. We all
Speaker 4: had computers, but we didn't have cell phones. I got
Speaker 4: my first cell phone after I graduated from college, like
Speaker 4: the year after, and I had a flip phone, and
Speaker 4: I thought that was super cool. You know, I could
Speaker 4: type out a text message one character at a time,
Speaker 4: oh T nine.
Speaker 3: Yeah, I had a gold medal in T nine. I
Speaker 3: nice could do it without even looking at the phone.
Speaker 3: Where I found it harder when we had a keyboard.
Speaker 4: Yeah, and then I had a palm pilot, like as
Speaker 4: the precursor to the iPhone. And then I stood in
Speaker 4: line the first day that the iPhone was being sold,
Speaker 4: and you know, got one of the first iPhones in
Speaker 4: my hands. So I've seen the evolution of tech, I
Speaker 4: guess as I was getting all of those degrees.
Speaker 3: And what about in terms of neurotechnology. Have you seen
Speaker 3: kind of an exponential growth path in terms of technology?
Speaker 3: Is that growth pattern still valid or have we surpassed it?
Speaker 4: Slowly? Over the past decade or two, neurotechnology has been
Speaker 4: getting better, and the ways in which neurotech has been
Speaker 4: getting better has largely been kind of hardware based, which
Speaker 4: is the centers are getting better. Sometimes the software has
Speaker 4: been getting better, to be able to filter out noise,
Speaker 4: the algorithms, to be able to pick up brain activity
Speaker 4: without having muscle twitches or eyeblinks or interference from the environment,
Speaker 4: to pick up different information. All that's been getting better.
Speaker 4: But suddenly we've gone from what was improvements to just
Speaker 4: the past five years seeing much more rapid advances. Generative
Speaker 4: AI is making things move in these seismic shifts, like
Speaker 4: where you suddenly have just a massive leap and capabilities.
Speaker 3: Just real quick, before we descend into the abyss of
Speaker 3: ethics and possible scenarios, what is generative AI? What is AA?
Speaker 3: And what's just a computer computing? Okay, I look this
Speaker 3: up for us, and then I took a nap because
Speaker 3: it was confusing, and then I tried again, and here's
Speaker 3: what I suessed out. So artificial means it's coming from
Speaker 3: a machine or software and intelligence fuck, I mean that
Speaker 3: depends on who you ask, but broadly it means a
Speaker 3: capacity for logic, understanding, learning, reasoning, problem solving, and retaining facts.
Speaker 3: So some examples of AI are googling or search engines,
Speaker 3: the software that recommends other things you might like to purchase,
Speaker 3: navigating via self driving cars. Your Alexa understanding when you
Speaker 3: scream Alexa stop because she tried to get YouTube subscribe
Speaker 3: to Amazon Prime Music again. It also includes computers being
Speaker 3: chess nerds that's AI and generating artwork. And according to
Speaker 3: some experts, AI can be separated into a few categories,
Speaker 3: including on the base level, reactive machines and those use
Speaker 3: existing information but they don't store or learning. Then there's
Speaker 3: limited memory AI that can use precedent to learn what
Speaker 3: choices to make. There's something called theory of mind AI
Speaker 3: and that can try to figure out the intentions of
Speaker 3: a user or even acknowledged their feelings, like if you've
Speaker 3: ever told Alexa to get bent in a lot of
Speaker 3: other words and then she sassas you back. If you'd
Speaker 3: like to tell me how I can improve, try saying
Speaker 3: I have feedback. There's also a type called self aware
Speaker 3: AI that reflects on its own actions, and then fully
Speaker 3: autonomous is kind of the deluxe model of AI, and
Speaker 3: that just that does its own thing, that sets its
Speaker 3: own goals, set it and forget it if you can.
Speaker 3: So when did things start speeding up? When did they
Speaker 3: start careening toward the future like this, When computers got
Speaker 3: faster and smaller and better in the last ten but
Speaker 3: really kind of two or three years. So better hardware
Speaker 3: means more processing power. There's also cloud storage, and that
Speaker 3: adds up to something called deep learning, which kind of
Speaker 3: sounds creepy like a hypervigilant mannequin, but deep refers to
Speaker 3: many layers of networks that use what look like these
Speaker 3: complicated flow charts to decide what actions to take based
Speaker 3: on previous learning. So that's kind of what led up
Speaker 3: to these startlingly human like generative AI outputs and deep
Speaker 3: fakes where they can just straight up put Keanu Reef's
Speaker 3: face on your mom and then confuse the the Jesus
Speaker 3: out of me on TikTok or chat GBT, which is
Speaker 3: one language model. Chatbot computers are starting to pass bar exams.
Speaker 3: Maybe they're writing the Quippi flirtations on your dating app.
Speaker 3: Who knows. Meanwhile, less than one hundred years ago, a
Speaker 3: lot of the US didn't have flush toilets. In case
Speaker 3: you feel weird about how weird this feels, because it
Speaker 3: is weird. Evolutionarily, our flabby, beautiful little brains can barely
Speaker 3: handle the shock of a clean river coming out of
Speaker 3: a garden. Hose let alone some metal and rocks that
Speaker 3: are computers that we're training to potentially kill us. We
Speaker 3: don't know how to deal with that.
Speaker 4: So pattern recognition using machine learning algorithms has really pushed
Speaker 4: things forward rapidly, like a lot of brain data that
Speaker 4: happens in characteristic patterns and those associations between like what
Speaker 4: does a person seeing or hearing or thinking? How are
Speaker 4: they feeling? Are they tired, are they happy? Are they sad?
Speaker 4: Or are they stressed? Those things have been correlated with
Speaker 4: huge data sets and processed using machine learning algorithms in
Speaker 4: ways that weren't.
Speaker 3: Possible before I can read your mind.
Speaker 4: Then you have generative AI and chat GBT that enters
Speaker 4: the scene in November, and all of a sudden, the
Speaker 4: papers that are coming out are jaw dropping. Data that's
Speaker 4: being processed by generative AI to reconstruct what a person
Speaker 4: is thinking or hearing or imagining or seeing. Is next level, right,
Speaker 4: I mean, you know, my book came out March fourteenth,
Speaker 4: twenty twenty three. All of a sudden, what was happening
Speaker 4: was continuous language decoding from the in like really really
Speaker 4: high resolution using GPT one, not even the most advanced
Speaker 4: GPT four visual reconstruction of images that a person is
Speaker 4: seeing in ways that were much more precise than anything
Speaker 4: that we had seen previously. And that's happening at this clip.
Speaker 4: That is just, I think extraordinary. It's just so much
Speaker 4: faster than I even I would have imagined, and even
Speaker 4: I could have anticipated, even having written a book about
Speaker 4: the topic, that was.
Speaker 3: Literally going to be my next question, because when a
Speaker 3: person writes a book that doesn't happen every night. Even
Speaker 3: working on this book, probably for a couple of years,
Speaker 3: did you have any idea that your book would be
Speaker 3: so closely timed to such a giant leap in terms
Speaker 3: of public perception and awareness of AI. I mean, couldn't
Speaker 3: have timed it better? Well?
Speaker 4: I mean, of course, I'm a futurist. I was predicting
Speaker 4: it perfectly right now, No, I mean I wish right
Speaker 4: In truth, my book is like a year and a
Speaker 4: half late from when I was supposed to turn it
Speaker 4: into the editor and to the publisher. But you know,
Speaker 4: there was a global pandemic that got in the way
Speaker 4: and a bunch of other things. But I'm grateful that
Speaker 4: it didn't happen sooner, because I was both able to
Speaker 4: be part of what is a growing conversation about the
Speaker 4: capabilities of AI, and to see when you say to
Speaker 4: a person like, oh yeah, also AI can decode your brain.
Speaker 4: You know, that really puts a fine point on it
Speaker 4: for people to understand how quickly these advances are coming
Speaker 4: and to see how it's changing everything in society, not
Speaker 4: just how people are writing essays or writing emails, but
Speaker 4: fundamentally unlocking the mysteries of the mind that people never
Speaker 4: thought before possible, and the risk that that opens up,
Speaker 4: and the possibilities of mental manipulation and hacking and tracking.
Speaker 4: Those are dangers that I think a year ago, before
Speaker 4: people really woke up to the risks of AI, they
Speaker 4: would not have been having the conversation in the same
Speaker 4: way that they are around the book. And now they
Speaker 4: are having that conversation seeing the broader context and seeing
Speaker 4: the alarm bells everywhere. Right, oh wait, we really do
Speaker 4: need to regulate or recognize them rights or do something.
Speaker 3: So futurists are urging some foresight. Congressional panels have aired
Speaker 3: on c SPAN and there seems to be this kind
Speaker 3: of collective side eye and like a hope someone's on
Speaker 3: top of this, right.
Speaker 4: So I mean, I think people are looking for some
Speaker 4: guidance and to have somebody come at it from a
Speaker 4: balanced perspective, like, wait a minute, there's a lot of
Speaker 4: good here, and there's some serious risks, and here's a
Speaker 4: potential pathway forward. I think, you know, instead of like pause,
Speaker 4: which everybody says like of course, we can't just pause,
Speaker 4: or you know, a doomsday scenario without any positive like oh,
Speaker 4: let's regulate AI, I think we need voices at the
Speaker 4: table who are thinking about it both in a balanced way,
Speaker 4: but also are coming forward with like here's some concrete
Speaker 4: things we could do right now that would actually help
Speaker 4: the problem.
Speaker 3: So we know a few types of AI, from googling
Speaker 3: a source for a research paper or digitally removing your
Speaker 3: cousins X from your wedding photos. But about technology that's
Speaker 3: gathering data from our brains.
Speaker 4: Let me give you the spectrum. There's medical grade neurotechnology.
Speaker 4: This is technology that people might imagine in a doctor's
Speaker 4: office where somebody puts on an EEG electro encepholography cap
Speaker 4: that has a bunch of different wires coming out of
Speaker 4: it and a bunch of gel that's applied to their head,
Speaker 4: and a bunch of sensors. That's picking up electrical activity,
Speaker 4: which we'll get back to in a minute. Then there's
Speaker 4: the clunky giant machine, a functional magnetic resonance imaging machine
Speaker 4: which can peer deeply into the brain. And somebody might
Speaker 4: have already undergone an fMRI test for something like a
Speaker 4: brain tumor to kind of look more deeply into the brain.
Speaker 4: And what that's picking up is changes in blood flow
Speaker 4: across the brain, which tells us something about different areas
Speaker 4: that are activated anyto particular time and what those patterns
Speaker 4: might mean.
Speaker 3: So if you've never had an MRI, I guess, congratulations,
Speaker 3: that's probably good. But this is magnetic resonance imaging and
Speaker 3: it's pretty exciting how these strong as magnets all line
Speaker 3: up the hydrogen atoms in your body to go one
Speaker 3: direction and then they release them and from that they
Speaker 3: can see inside of your boudet. Now, an fMRI is
Speaker 3: a functional MRI, and to put it in super simple terms,
Speaker 3: it's kind of like animation instead of a still picture,
Speaker 3: but it's of your brain. So when you see imaging
Speaker 3: examples of how someone's melon illuminates like a Christmas tree
Speaker 3: to a certain stimuli, that's fMRI technology tracking blood flow to
Speaker 3: different regions of the brain. And this fMRI technology is
Speaker 3: used in a lot of neuro and psychology research.
Speaker 4: And then there's something like functional near infrared spectroscopy, which
Speaker 4: is more portable and it's also measuring changes in the brain,
Speaker 4: but it's using optical and infrared lights in order to
Speaker 4: do so.
Speaker 3: And that functional near infrared spectroscopy looks for changes in
Speaker 3: oxyhemoglobin and deoxyhemoglobin in the brain. It might not matter
Speaker 3: to you right now as you're cleaning your shower grout
Speaker 3: or your carpooling, but in clinical settings it comes in
Speaker 3: handy for patients with strokes, or learning about Alzheimer's or Parkinson's,
Speaker 3: or even anxiety or a traumatic brain injury, which my
Speaker 3: brain would like you to know I've had, and I
Speaker 3: will link the traumatic brain injury or the neuropathology episode
Speaker 3: about my hell and Narnar concussion I got last year
Speaker 3: in the show notes. But yes, there are a lot
Speaker 3: of ways to get data from a brain, including T
Speaker 3: scans and PET scans with radioactive tracers. But what about
Speaker 3: non medical uses? Do they exist? Oh?
Speaker 4: Boy, how do you do they? If you then look
Speaker 4: at what's happening in the consumer space. And the consumer space,
Speaker 4: you take the sixty four one hundred and twenty electrodes
Speaker 4: that are in a big cap, and then you have
Speaker 4: a couple of them that are put into a forehead
Speaker 4: band or a baseball cap, or increasingly, what's coming is
Speaker 4: brain sensors that are embedded in everyday technology. So you
Speaker 4: and I are both wearing headphones, and the soft cups
Speaker 4: that go around our ears are being packed with sensors
Speaker 4: that can pick up brain activity by reading the electrical
Speaker 4: activity through our scalp. You want my tinfoil hat, or
Speaker 4: if we were wearing earbuds inside of our ears, instead
Speaker 4: embedding brain sensors inside of those that can pick up
Speaker 4: electrical activity in our brain activity as we're thinking or
Speaker 4: doing anything, and those become much more familiar and much
Speaker 4: more commonplace very quickly. So there's just a few of
Speaker 4: those products that are on the market, but that's where
Speaker 4: most of the big tech companies are going, is to
Speaker 4: embed brain sensors into everyday devices like earbuds and headphones
Speaker 4: and even watches that pick up brain activity from your
Speaker 4: brain down your arm to your wrist and picks up
Speaker 4: your intention to move or to type or to swipe
Speaker 4: or something like that.
Speaker 3: So to use like a medical analogy. You know, continuous
Speaker 3: glucose monitors. These are a powerful tool for diabetics to
Speaker 3: monitor their blood sugar levels and their insulin needs, and
Speaker 3: we cover those in the two part Dibetology episode with
Speaker 3: doctor Mike Natter. But now continuous glucose monitors are starting
Speaker 3: to become available to people without diabetes just to better
Speaker 3: understand their metabolisms and their dietary responses, their mood and energy.
Speaker 3: So all of these neuroimaging and all this data was
Speaker 3: just used in clinical and research settings by people in
Speaker 3: crisp coats carrying metal clipboards, but it's starting to pop
Speaker 3: up in the market. Now. This is great news, right
Speaker 3: understanding your brain? Yeah yeah, But not all the research
Speaker 3: in consumer applications is solid, and some make some wild
Speaker 3: claims of efficacy. Others argue that if a device can
Speaker 3: enhance our moods and sharpen us cognitively but cost some
Speaker 3: serious cash, doesn't that just widen a privileged gap even further?
Speaker 3: But I guess so does college. I don't know. In
Speaker 3: the US, you need a GoFundMe to pay for chemo,
Speaker 3: so we've got a lot of pretty large systemic fish
Speaker 3: to fry. But if you've got money, you can buy
Speaker 3: EEG headsets that track your mood and emotions and stress
Speaker 3: for a few grand. There's others that track your heart
Speaker 3: rate and brain waves for sleep and meditation. There are
Speaker 3: VR gaming sets that track brain waves, and even a
Speaker 3: matel game called mind Flex you can buy for like
Speaker 3: one hundred and twenty bucks.
Speaker 4: But Nita says, all of those consumer based technologies pick
Speaker 4: up a little bit of like kind of low resolution
Speaker 4: information right now. They pick up if you're stressed, if
Speaker 4: you're happy, or if you're sad, if you're tired, like
Speaker 4: it maybe picks up that your mind is wandering and
Speaker 4: you're you know, kind of like dozing off. And the
Speaker 4: things like fMRI pick up much more precise information. Now
Speaker 4: that could just be a matter of time. It could
Speaker 4: be that as machine learning algorithms and gender tove AI
Speaker 4: gets up and get applied to the electrical activity in
Speaker 4: the brain, that it'll get better and better and better.
Speaker 4: And it's interesting because in a way you could think
Speaker 4: about AI as being the convergence between computer science and neuroscience.
Speaker 4: So computer scientists have been designing algorithms that can process
Speaker 4: information in very narrow ways and they're very good at
Speaker 4: doing specific tasks. So, for example, a doctor or a
Speaker 4: pathologist who's looking at many different samples of tissue to
Speaker 4: figure out if it looks cancerous or not can only
Speaker 4: see so many samples in a lifetime, and so they've
Speaker 4: marked them and labeled the data, and a machine learning
Speaker 4: algorithm can be trained on that data, which is like,
Speaker 4: here's thousands of images that are cancer and not cancer.
Speaker 4: Now here are new images predict whether or not they
Speaker 4: have cancer, And they become very very good because they
Speaker 4: can process millions and millions of images and see far
Speaker 4: more images and get much better at being able to
Speaker 4: do that specific task of identify if something as cancerous.
Speaker 3: So those tasks are relatively simple for machines to learn
Speaker 3: and execute. Computers are like child's play, but.
Speaker 4: The human brain isn't so narrow in task specific and
Speaker 4: neuroscience has long understood that the connections that the brain
Speaker 4: makes are much more multifaceted, they're much more complex, and
Speaker 4: so the modern types of AI are built on how
Speaker 4: the brain works. They're built on what are called neural networks.
Speaker 4: So this is a deep learning model which is instead
Speaker 4: of that very specific task of like do this, do that,
Speaker 4: it's meant to take a huge amount of information to
Speaker 4: learn from that information and then do what we do,
Speaker 4: which is to predict the next thing, or to kind
Speaker 4: of understand where that's going, or to make inferences from
Speaker 4: more of a deep learning perspective.
Speaker 3: So it's more than machine learning like the pathology example
Speaker 3: she gave. So remember deep learning. So neural networks are
Speaker 3: modeled after biological brains, and they have nodes like neurons
Speaker 3: that consume input that they learn from, and then it's
Speaker 3: processed in several layers or tiers, aka it's deep to
Speaker 3: come up with a result or an action. And things
Speaker 3: like chatbox or facial recognition or typing dog into your
Speaker 3: phone's photo album to see what goodness comes up, we're
Speaker 3: speech to text. Those are all done by neural networks
Speaker 3: and AI that we're already using, and they seem commonplace
Speaker 3: after having them for just a few years. But since
Speaker 3: late last year, we're seeing them create more like how
Speaker 3: the human brain might.
Speaker 4: And those insights about the brain and neural networks have
Speaker 4: informed this new class of AI, which is generative AI.
Speaker 4: Generative AI is different in that it is both built
Speaker 4: on a different model and it has much greater flexibility
Speaker 4: in what it can do. And it's trying to not
Speaker 4: say like this is cancer, that isn't cancer, but to
Speaker 4: take a bunch of information and then be asked a
Speaker 4: question and to respond or to generate much more like
Speaker 4: the human brain reasons or thinks or comes up with
Speaker 4: the next solution. And that's exciting and terrifying.
Speaker 3: Also, what about the that say, the artistic AI is
Speaker 3: getting are they scrubbing that from existing art And in
Speaker 3: the case of say the writers strike, where you see
Speaker 3: writers saying you cannot take my scripts and write a
Speaker 3: sequel on something, yeah, without me. And if you're curious
Speaker 3: about what is up with these strikes, what is going
Speaker 3: on in the entertainment industry, including the WGA or the
Speaker 3: Writers Skilled of America strike which started on May Day
Speaker 3: this year and it was joined in recent weeks on
Speaker 3: the picket lines by sag Aftra, which is a screen
Speaker 3: actor skilled And again we did a whole episode explaining
Speaker 3: what is going on. It's called Field Trip WGA Strike
Speaker 3: that'll be linked to the show notes. So if you
Speaker 3: watch TV or movies or you ever have listened to
Speaker 3: that episode because it affects us all, and these entertainment
Speaker 3: labor unions are known as the tip of the spear
Speaker 3: for other labor sectors. Your industry may be affected or
Speaker 3: might be next.
Speaker 4: I'm really interested in what happens in this space, just
Speaker 4: because of the writers themselves and hoping that they managed
Speaker 4: to succeed in actually getting fair appropriate treatment, but also
Speaker 4: because it's going to be incredibly telling for every industry
Speaker 4: as what happens when workers demand better conditions and better terms,
Speaker 4: and the result is greater experimentation. We generative AI to
Speaker 4: replace them.
Speaker 3: But why is this such a sudden concern? Why does
Speaker 3: it feel like AI has just darkened the horizon and
Speaker 3: thundered into view and we're all cowering at its advance?
Speaker 3: Is this the first act of a horror film?
Speaker 4: So how where does it come from? They're not totally transparent.
Speaker 4: We don't know all of the answers to that, right,
Speaker 4: But we do know that these models have been trained,
Speaker 4: meaning there's been billions potentially trying as we don't know
Speaker 4: right the exact number of parameters. That is prior data
Speaker 4: which has been used.
Speaker 3: Meaning the material that the machines learned from.
Speaker 4: And that could be prior scripts, it could be prior books.
Speaker 4: It includes a bunch of self published books apparently that
Speaker 4: are part of it, prior music, prior art, potentially a
Speaker 4: whole lot of copyrighted material that has been used to
Speaker 4: inform the models. Once the models learn, they're not drawing
Speaker 4: from that information anymore. Right, that information was used to
Speaker 4: train them, but in the same way that you don't
Speaker 4: retain everything you've ever read or listened to, and your
Speaker 4: creativity may be inspired by lots of things that you've
Speaker 4: been exposed to. The models are similar and that they've
Speaker 4: been trained on these prior parameters, but they're not storing
Speaker 4: or drawing from or returning to them. It's as if
Speaker 4: they have read and digested all of that information. And
Speaker 4: I was talking with an IP scholar who I like
Speaker 4: and respect very much, and his perspective was, how is
Speaker 4: that different than what you do? Right? You write a
Speaker 4: book and you read tons of information, and there's tons
Speaker 4: of information you cite, and there's also tons of information
Speaker 4: that you learned from that inspired you, that shaped how
Speaker 4: you write and think that you don't actually cite. And
Speaker 4: is that actually unfair or violating the intellectual property or somehow,
Speaker 4: you know, not giving a fair shake to every source
Speaker 4: that you have ever learned from or every input that
Speaker 4: you've ever learned from. I mean, it's an interesting and
Speaker 4: different perspective, right, I don't have the answers to it yet.
Speaker 4: I'm really interested to see how this particular debate evolves.
Speaker 3: What do other people think who aren't me? So a
Speaker 3: recent study reported that about fifty percent of AI experts
Speaker 3: think there's a ten percent chance of unchecked AI causing
Speaker 3: the extinction of our species, with AI getting into a
Speaker 3: little sneaky elf on the shelf shenanigans like playing god
Speaker 3: or establishing a political dictatorship. And the Center for AI
Speaker 3: Safety issued a statement. It was signed by dozens of
Speaker 3: leaders in computer science and tech, including the CEO of
Speaker 3: Google's Deep Mind and Bill Gates and the guy who
Speaker 3: started jat GPT and the director of a center on
Speaker 3: Strategic Weapons and Strategic Risks. And this statement said, very
Speaker 3: simply quote, mitigating the risk of extinction from AI should
Speaker 3: be a global priority alongside other societal scale risks such
Speaker 3: as pandemics and nuclear war. So that's a pretty big statement.
Speaker 3: And other experts draw parallels between humans and chimps but
Speaker 3: where the chimps and AI is us? So guess who's
Speaker 3: making who wear diapers and live with Michael Jackson. Yeah, although,
Speaker 3: of course there are computer scientists saying that we need
Speaker 3: to calm our collective boobies and that AI isn't advanced
Speaker 3: enough to threaten us yet Yet I love yet?
Speaker 5: Yet?
Speaker 3: Is so comfy? Yet? Is the space between the alarm
Speaker 3: clock and the panic of racing out the door because
Speaker 3: you'll be laid to a job interview?
Speaker 4: Ah?
Speaker 3: Yet? Yummy? Just fuck it.
Speaker 4: I think from a governance perspective, in society we have
Speaker 4: near term risk that we need to be safeguarding against.
Speaker 4: And this is near term risk like bias and discrimination
Speaker 4: and inaccuracies. I don't know if you saw the story
Speaker 4: recently about a lawyer who filed a brief in a
Speaker 4: case before a federal judge that the pleading for the
Speaker 4: case had been entirely written by CHATTEBT, which included a
Speaker 4: whole bunch of invented cases, and the invented cases like
Speaker 4: he hadn't gone and site checked them or read them.
Speaker 4: In fact, he has this dialogue where he's asking chatbt
Speaker 4: if the cases are real or not.
Speaker 3: It's rather than like and he was not doing this
Speaker 3: to prove a point.
Speaker 4: No, straight up, just like straight up dumbass, just did it,
Speaker 4: I mean, and like then the other side comes back
Speaker 4: and says like, hey, judge, we can't find any of
Speaker 4: these cases. And the judge says, like, you have to
Speaker 4: produce it, and apparently he produces the full citations of
Speaker 4: the made up cases and anyway, it finally goes back
Speaker 4: with the lawyer that admitting like, I'm so sorry, this
Speaker 4: is all apparently, you know, fabricated, and it's fabricated, not intentionally,
Speaker 4: but it's fabricated because I generated at all using chat GPT.
Speaker 3: Nita says, who knows what will happen if and when
Speaker 3: more people start using bots to kind of cut corners
Speaker 3: and know in fact checks it. And around juneteenth, I
Speaker 3: saw a viral tweet about chat GPT not acknowledging that
Speaker 3: the Texas and Oklahoma border was in fact influenced by
Speaker 3: Texas desiring to stay a slave state. I told my husband, Jared,
Speaker 3: your pod mom didn't believe it could get things so wrong,
Speaker 3: And then he proceeded to have like an hour long
Speaker 3: fight and discussion with chat GPT, hoping to teach chat
Speaker 3: GPT that it has a responsibility to deliver accurate information.
Speaker 3: I was like, dude, you're fighting a good fight, and
Speaker 3: I wish you luck. Now. As for this lawyer that
Speaker 3: Nita mentioned, according to a May twenty twenty three New
Speaker 3: York Times piece about it titled Here's what happens when
Speaker 3: your lawyer uses chat GPT, the lawyer in question pleaded
Speaker 3: his own case within the case, telling a rightfully miffed
Speaker 3: off judge that it was his first foray with a
Speaker 3: chatbot and that he was quote therefore unaware of the
Speaker 3: possibility that its content could be false. And The New
Speaker 3: York Times explains that chatchbt generates realistic responses by making
Speaker 3: guesses about which fragments of text should follow other sequences,
Speaker 3: based on a statistical model that has ingested billions of
Speaker 3: examples of text pulled from all over the Internet. So
Speaker 3: chatgbt is your friend at the party who knows everything,
Speaker 3: and then you find out that they're full of shit
Speaker 3: and they're very drunk, and maybe they stole your wallet
Speaker 3: and they could kill your dog. Will they shit in
Speaker 3: the pool? It's anyone's guess. But wow, they are spicing
Speaker 3: up the vibe. This is not a boring party at all.
Speaker 4: It raises this complex question about you know, who is responsible,
Speaker 4: and we've generally said the attorney is responsible, right. The
Speaker 4: attorney is the one who is licensed to practice law.
Speaker 4: They're responsible for making sure all of the work that
Speaker 4: they certify under their name. Is there any liability for
Speaker 4: generative AI models? Now? CHATGBT says like, I'm not here
Speaker 4: to provide legal advice and it's prone to hallucinations. Is
Speaker 4: that enough to disclaim any liability for chat GBT?
Speaker 3: Just a chacouzie of hallucinating chatbots saying whatever sentence they
Speaker 3: think you want to hear. Maybe pooping in there too.
Speaker 3: So what happened to that Laurie though? Did he get
Speaker 3: so disbarred? Did he have to grow a beard and
Speaker 3: move to Greenland? Does he make felted hats out of
Speaker 3: goat for now? No? No, he's fine. He kept his job.
Speaker 3: He was just fined five grand, which if he build
Speaker 3: for the research hours that a chatbot really did, he
Speaker 3: maybe still turned to profit on that deal. But the
Speaker 3: lessons those are invaluable now if you appreciate nothing else today,
Speaker 3: I just want you to stare off at the horizon
Speaker 3: for even thirty seconds and just say, what a time
Speaker 3: we're living in hundreds of thousands of years of people
Speaker 3: and boners and falling in love made me a person
Speaker 3: standing on a planet at a time when there's plumbing, antibiotics, electricity,
Speaker 3: there's domesticated cats, and I have a front row seat
Speaker 3: to some real madness. What an era as for what
Speaker 3: we do? I don't know. Aren't we being watched all
Speaker 3: the time anyway? What are the watchers doing about this? Well,
Speaker 3: forgive the patriarchal caricatures, but where are big brother and
Speaker 3: Uncle Sam? Are they working together on this? Is there
Speaker 3: any incentive from like a governance perspective to say to
Speaker 3: step in and say, like, we don't know how far
Speaker 3: this should go? Or does it just generate kind of
Speaker 3: more income for maybe big corporations that can misuse it?
Speaker 3: So like m hard to fight against that.
Speaker 4: So you know, it's hard to know, right. There have
Speaker 4: been hearings that have been held recently by the government
Speaker 4: to try to look into sort of both questions that
Speaker 4: you're asking, which is Uncle Sam and Big Brother. So
Speaker 4: there were hearings looking at whether or not to regulate
Speaker 4: private corporation use of generative AI models, and it was
Speaker 4: very public hearing where Sam Altman from open Ai calls
Speaker 4: for regulation.
Speaker 3: If you're wondering why this is a big deal. So
Speaker 3: Sam Altman is the CEO of open Ai, which invented
Speaker 3: chat GPT, and he spoke at the Senate Judiciary sub
Speaker 3: Committee on Privacy, Technology and the Law hearing which was
Speaker 3: called Oversight of AI Rules for Artificial Intelligence that was
Speaker 3: in May of this year. He also signed that statement
Speaker 3: about trying to mitigate the risk of extinction, and he
Speaker 3: told the committee that AI could quote cause significant.
Speaker 4: Harm to the world.
Speaker 3: Papa chat GPD.
Speaker 6: Himself, my worst fears are that we cause significant we
Speaker 6: the field, the technology, the industry caused significant harm to
Speaker 6: the world. I think that could happen in a lot
Speaker 6: of different ways. I think if this technology goes wrong,
Speaker 6: it can go quite wrong, and we want to be
Speaker 6: vol cool about that. We want to work with the
Speaker 6: government to prevent that from happening.
Speaker 3: And ultimately Sam urged the committee to help establish a
Speaker 3: new framework for this new technology.
Speaker 4: It was a surprisingly collaborative tone for most of the
Speaker 4: federal officials who were questioning him, very differently than in
Speaker 4: social media context of the past.
Speaker 3: But meanwhile, in a different building.
Speaker 4: That same day, a different hearing was happening which most
Speaker 4: people weren't aware of, which was federal use of AI,
Speaker 4: and a lot of the discussion in that context was
Speaker 4: about how the federal government needs to be innovating, to
Speaker 4: use more AI in a lot of what they do,
Speaker 4: and to be monetizing.
Speaker 1: What's happening today, we'll be discussing how AI has the
Speaker 1: potential to help government serve better serve the American people.
Speaker 3: Okay, so tonally, the Senate Homeland Security and Governmental Affairs
Speaker 3: Committee hearing, which was called Artificial Intelligence and Government, was
Speaker 3: a little bit more optimistic, like, I give me some
Speaker 3: of that.
Speaker 4: And that would include things like Uncle Sam, right, improving
Speaker 4: the IRS system, and you know what does filing of
Speaker 4: taxes look like? And are there ways to ease the burden?
Speaker 4: Are there are ways to modernize and have different parts
Speaker 4: of the government talking to each other, and hopefully those
Speaker 4: conversations will converge. We won't be looking at like how
Speaker 4: do we regulate and limit the rests of generative AI
Speaker 4: and then infuse it throughout all of the federal government
Speaker 4: at the same time, right, and hopefully like you have
Speaker 4: the left hand talking to the right hand, so that
Speaker 4: we actually come up with a sensible strategy and a
Speaker 4: road ahead.
Speaker 3: A road ahead, But which one are you feeling confused
Speaker 3: right now? Because you should be the inventors and the
Speaker 3: backers of a billion dollar technology swore under oath something
Speaker 3: to the tune of, yeah, man, this shit could kill us.
Speaker 3: And everyone's freaking out because it's already taking over jobs
Speaker 3: because it's so smart. But at the same time, it's
Speaker 3: worse at googling than your ten year old niece with
Speaker 3: a book report. And while this is going on, the
Speaker 3: government is holding two simultaneous hearings on the same day,
Speaker 3: and one is Oppenheimer flavored and the other is Barbieland
Speaker 3: so if you are confused by all of this and
Speaker 3: you don't know how to feel, the answer is, yes,
Speaker 3: that's correct.
Speaker 4: But it's happening so quickly that it's not going to
Speaker 4: be law alone that does anything to rein it in.
Speaker 4: We're going to need a lot of cooperation between governments,
Speaker 4: between tech companies. And you know, if you look in
Speaker 4: the US, the US has not been good at regulating
Speaker 4: tech companies, right. I mean, it has had lots of
Speaker 4: talk about it, lots of very contentious Senate hearings.
Speaker 6: I started Facebook, I run it, and I'm responsible for
Speaker 6: what happens here.
Speaker 4: And then they have so much money and so much
Speaker 4: power and so much lobbying influence that you know the
Speaker 4: result is nothing happens. And that just can't be the case. Now,
Speaker 4: we can't go into this era leaving it up to
Speaker 4: tech companies to decide the fate of humanity.
Speaker 3: Right, what do you do if you're mad as hellan
Speaker 3: you're not going to take it anymore? What is an
Speaker 3: average person who does not own a forty billion dollar
Speaker 3: tech company say when they're like, don't scrub my brain
Speaker 3: data through my headphones, I'd stop simulating art. Let some
Speaker 3: people make some art. Have you seen that meme about how,
Speaker 3: somehow we've gotten to a place where human beings are
Speaker 3: still laboring at wages that don't increase, that are not liveable,
Speaker 3: and yet computers get to write poetry and make art. No,
Speaker 3: but that sounds right, that's such a heartbreaking way to
Speaker 3: look at it, where no one can afford to be
Speaker 3: an artist. So the exact words from Twitter user Carl
Speaker 3: Cherrow read humans doing the hard jobs on minimum wage
Speaker 3: while the robots write poetry and paint is not the
Speaker 3: future I wanted. So that tweet was shared thirty five
Speaker 3: thousand times because it's true and it hurts my soul.
Speaker 4: You know, I haven't seen that meme and now I'm
Speaker 4: reeling from thinking about it, which is like, oh my god,
Speaker 4: that's so true. Suddenly we've like we've outsourced all the
Speaker 4: things that we like and we're now doing all of
Speaker 4: the grunt work still, and like, how horrible is that?
Speaker 4: Going to send like generative AI to the beach next
Speaker 4: weekend and so you know, like what we like, stay
Speaker 4: home and toil and pay for it, right, Yeah, I mean,
Speaker 4: you know. The problem is that on the one hand,
Speaker 4: we could say like, oh, it's all happening so quickly
Speaker 4: and so we can't do anything about it. On the
Speaker 4: other hand, that's just the nature of emerging tech. It
Speaker 4: happens quickly, and so it's not as if there have
Speaker 4: not been proposals about what agile governance looks like or
Speaker 4: what adaptive regulations look like that actually change based on
Speaker 4: changes in milestones and technology, and it would not be
Speaker 4: impossible to put some of those things into place. There
Speaker 4: have been people who've been writing about and thinking about
Speaker 4: and proposing these models for a long time.
Speaker 3: First off, what does agile governance look like and what
Speaker 3: does adaptive regulations mean? I don't know. I'm not a
Speaker 3: law professor. I'm a podcast host who's jealous of a
Speaker 3: circuit board that gets to a watercolor. So I asked
Speaker 3: my robot machine Google and agile governance means a process
Speaker 3: that brings the most value by focusing on what matters. Okay,
Speaker 3: But adaptive regulation I think mean like, watch this space,
Speaker 3: keep making laws if shit seems like it's getting out
Speaker 3: of hand now. In June, the European Union overwhelmingly passed
Speaker 3: the EUAI Act, which classifies different types of AI into
Speaker 3: risk categories. There's unacceptable, there's high risk, there's generative AI,
Speaker 3: and limited risk. What is in these buckets, you're wondering.
Speaker 3: So the unacceptable bucket includes cognitive behavioral manipulation and social
Speaker 3: scoring a LA Black mirror, and biometric identification like real
Speaker 3: time public facial recognition. High risk involves more biometric uses,
Speaker 3: but after the fact, with a few exceptions for law enforcement.
Speaker 3: But it curbs AI snitching on employees and doing emotional
Speaker 3: spying from one together. Generative AI would have to disclose
Speaker 3: that is generative, and the makers need to come clean
Speaker 3: on what copyrighted material they're using to teach generative neural networks. Now,
Speaker 3: that's it the EU. As for America, we have not
Speaker 3: gotten that far yet. I mean that is, if everyone
Speaker 3: could even agree on what needs to happen, then they'd
Speaker 3: have to agree on voting for that thing to be
Speaker 3: actually enacted, which is it's a beautiful dream that I'm
Speaker 3: generating with my human imagination.
Speaker 4: The problem has been, I think, the political will to
Speaker 4: do anything about it and to figure out, like, why
Speaker 4: should we care about the cognitive liberty of individuals, Why
Speaker 4: should we care about leisure and flourishing of humanity? Let's
Speaker 4: just maximize productivity and minimize human enjoyment in life. That
Speaker 4: just can't be what the answer is in the digital
Speaker 4: age anymore, right, I mean, we need an updated understanding
Speaker 4: of what flourishing means. And it can't be that it
Speaker 4: is generative AI making art and writing poetry while we
Speaker 4: toil away, Right, that can't be the case. Like I'm
Speaker 4: a philosopher, right, I'm going to go back to We
Speaker 4: have all of these philosophical conceptions, lots of perspectives on
Speaker 4: what flourishing is none of those perspective if you go
Speaker 4: back and look at them, contemplated a world in which
Speaker 4: our brains and mental experiences could so easily be hacked
Speaker 4: and manipulated, and the idea of happiness being the primary
Speaker 4: concept of human flourishing, Like, what is synthetic happiness? Is
Speaker 4: that really happiness? If it's generated by dopamine hits from
Speaker 4: being on a predictive algorithm that's sending you little notifications,
Speaker 4: it's just the right time to make your brain addicted
Speaker 4: and staying in place that looks like happiness. But I
Speaker 4: don't think that's happiness, right, right, So, given that all
Speaker 4: of these presupposed world in which we actually had cognitive freedom,
Speaker 4: we need to realize we don't anymore, right, And if
Speaker 4: we don't anymore, we need to create a space in
Speaker 4: which we do so that human flourishing in the digital
Speaker 4: age is what we're actually after and trying to make happen.
Speaker 4: That we could put some human rights in place for it,
Speaker 4: We could put some systems in place that we're actually
Speaker 4: creating incentives to maximize cognitive freedom as the precursor to
Speaker 4: all other forms of flourishing, and hopefully that cognitive freedom
Speaker 4: would be the right to create art without having it appropriated,
Speaker 4: the right to write scripts and poetry without having it
Speaker 4: used to train models without our permission and without us
Speaker 4: being part of it. That then make us irrelevant, so
Speaker 4: that the models can play while we work.
Speaker 3: So in her book The Battle for Your Brain, Needa
Speaker 3: writes that we must establish the right to cognitive liberty
Speaker 3: to protect our freedom of thought and rumination, mental privacy,
Speaker 3: and self determination over our brains and mental experiences. This
Speaker 3: is the bundle of rights that makes up a new
Speaker 3: right to cognitive liberty, which can and should be recognized
Speaker 3: as part of the Universal Declaration of Human Rights, which
Speaker 3: creates powerful norms. They guide corporations and nations on the
Speaker 3: ethical use of neurotechnology. Neurotechnology has an unprecedented power to
Speaker 3: either empower or oppress us. The choice is ours end quote.
Speaker 3: And one liberty I've taken is never using chat GPT.
Speaker 3: Kind of like my high school's football rallies. I I
Speaker 3: just don't want to participate, and I don't like what
Speaker 3: it's all about, even though literally no one cares. That
Speaker 3: is stinky drama student with dyed black hair embraces as boycotting.
Speaker 3: Nobody misses me I've always been a little bit creeped
Speaker 3: out and hesitant, like I've never tried chat GPT, and
Speaker 3: I have this absolutely incorrect illusion that if I don't
Speaker 3: use chatgept, it won't get smarter, and therefore I, single
Speaker 3: handedly by abstaining, have somehow taken down an entire industry
Speaker 3: of AI. It's not true.
Speaker 4: Well, it's not true, but there is something to this
Speaker 4: idea that we're not helpless and that there is a
Speaker 4: demand side to technology, just as there is a supply
Speaker 4: side to technology, and there is a sense in which
Speaker 4: consumers and individuals feel like they're helpless. It's the same
Speaker 4: way you see with voting, Well, what's the point of voting?
Speaker 4: Because my state always goes this way or that way
Speaker 4: or and that kind of apathy means that a lot
Speaker 4: of times elections are decided by everybody else, and you
Speaker 4: know that you don't have an effect. But this is
Speaker 4: even more so, like collectively, if we don't like the
Speaker 4: terms of service, why are we all still on the platforms?
Speaker 4: And you're right, the models are going to continue to
Speaker 4: be trained with or without you.
Speaker 3: Yeah, no, Like it's not that radical an act for
Speaker 3: just me to abstain.
Speaker 4: Well, but that idea that collectively we could act differently.
Speaker 4: If we could motivate and actually work collectively to act differently,
Speaker 4: we could act differently. One individual person silently protesting against
Speaker 4: chat GPT isn't going to do it right, but loudly
Speaker 4: protesting against it and saying like, look, the models train
Speaker 4: based on human interaction, and the more human interaction there is,
Speaker 4: the more it is trained, and so do you want
Speaker 4: to continue to feed into that model? That's a worthwhile
Speaker 4: societal conversation to have, you.
Speaker 3: Know, I was talking to my husband this morning about
Speaker 3: how many brilliant engineers end up working for bomb companies
Speaker 3: because they're going to have the best benefits, They're going
Speaker 3: to have the most stable employment. Right. How many people
Speaker 3: in the legal field do you feel like get kind
Speaker 3: of scooped up by tech companies because it's just an
Speaker 3: easier way to live. Do tech companies just have more
Speaker 3: pull to get the best lawyers to advocate for them
Speaker 3: instead of, for say, greater humanity.
Speaker 4: I think it's not just law right. If I look
Speaker 4: at some of the best tech ethicists, many of them
Speaker 4: have gone in house to a lot of companies that
Speaker 4: are not actually that invested in tech ethics, and many
Speaker 4: of them got laid off, and the major tech layoffs
Speaker 4: that have happened from twenty twenty two to twenty twenty
Speaker 4: three because a lot of tech companies I think have
Speaker 4: put lip service to being serious about ethics, but they
Speaker 4: haven't as seriously grappled with it. And the money and
Speaker 4: the power that these corporations have and the influence on
Speaker 4: society they have, I think both makes it hard for
Speaker 4: some people to resist saying no. But also this idea
Speaker 4: that like, if you're at a tech company where the
Speaker 4: transformation of humanity is happening, maybe you can steer it
Speaker 4: in the ways that you think are better for humanity.
Speaker 3: Are there any nonprofits or organizations that you feel like
Speaker 3: are doing a good job.
Speaker 4: There are a lot. I mean, I couldn't even begin
Speaker 4: to name them all. Like I would say, first, I
Speaker 4: admire what UNESCO is doing. So.
Speaker 3: UNESCO is the United Nations Educational, Scientific, and Cultural organization,
Speaker 3: and on their Ethics of Artificial Intelligence web page, it
Speaker 3: states UNESCO has delivered global standards to maximize the benefits
Speaker 3: of scientific discoveries while minimizing the downside risks, ensuring they
Speaker 3: contribute to a more inclusive sustainable and peaceful world. And
Speaker 3: it's also identified challenges and the ethics of neurotechnology. So
Speaker 3: as a result, their recommendation on the Ethics of Artificial
Speaker 3: Intelligence was adopted by one hundred and ninety three member
Speaker 3: states at UNESCO's General Conference way back in the olden
Speaker 3: times of November twenty twenty one.
Speaker 4: They're really trying to get out ahead of a lot
Speaker 4: of issues and to thoughtfully provide a lot of ethical
Speaker 4: guidance on a lot of different issues. I think the
Speaker 4: OECD is trying to be a useful and balanced organization
Speaker 4: to bring important information to bear.
Speaker 3: The OECD, I had to look this up, is the
Speaker 3: Organization for Economic Cooperation and Development and it's headquartered in
Speaker 3: France but involves thirty eight countries. So what are they doing.
Speaker 3: The OECD principles on Artificial Intelligence promote AI that's innovative
Speaker 3: and trustworthy and that respects human rights and democratic values.
Speaker 3: And then of course there's the EU.
Speaker 4: I think the EU is acting in ways that are
Speaker 4: really pushing the conversations forward around the regulation of AI
Speaker 4: and how to do it and how to respect everything
Speaker 4: for mental privacy, to safeguard against manipulation, and you know,
Speaker 4: they get lambasted for like going too far or not
Speaker 4: going far enough, and those conversations were better than putting
Speaker 4: nothing on the table, which is what's happening a lot
Speaker 4: of times in the US. I think the Biden administration
Speaker 4: has put out a lot of different principles that have
Speaker 4: been helpful, and that those kinds of principles are things
Speaker 4: around like an AI Bill of rights.
Speaker 3: I went and took a gander at this dock, and
Speaker 3: the blueprint for an AI Bill of Rights sets forth
Speaker 3: five principles which I will now read to you. You
Speaker 3: should be protected from unsafe or ineffective systems. You should
Speaker 3: not face discrimination by algorithms. You should be protected from
Speaker 3: abuse of data practices, and you should have agency over
Speaker 3: how data about you is used. You should know that
Speaker 3: an automated system is being used and understand how and
Speaker 3: why it contributes to outcomes that impact you. And finally,
Speaker 3: you should be able to opt out where appropriate and
Speaker 3: have access to a person who can quickly consider and
Speaker 3: remedy problems you encounter. I don't know if that means
Speaker 3: a helpline. I have no idea, but that five point
Speaker 3: framework is accompanied by a handbook called From Principles to practice,
Speaker 3: and it's guidance for anyone who wants to incorporate those
Speaker 3: protections into policy. So that's what the White House is
Speaker 3: put out. They're like, y'all, we should really like be
Speaker 3: cool and nice about all this. And it's so sweet,
Speaker 3: and I appreciate it. My grandma had eleven children and
Speaker 3: really just dozens of grandkids, and she still remembered all
Speaker 3: her birthdays and would send a letter with one dollar
Speaker 3: in it, and that dollar meant a lot, even if
Speaker 3: it didn't get you far in the world. But I
Speaker 3: appreciated it in the same way I appreciate that AI
Speaker 3: Bill of Rights. It's very sweet. I don't know what
Speaker 3: to do with that.
Speaker 4: There's a lot of different people coming at the problem
Speaker 4: from a lot of different perspectives. If anything, there are
Speaker 4: so many voices at the table that it's in many
Speaker 4: ways becoming noisy where we're not necessarily like moving ahead
Speaker 4: in a really constructive and productive way. And there's a
Speaker 4: lot of replication of efforts. But that's better than having
Speaker 4: too little activity at the table.
Speaker 3: So yeah, I think that a lot of us on
Speaker 3: the outside of it think there's a tumble weed blowing
Speaker 3: through a boardroom and nobody cares, so it's really good
Speaker 3: to hear.
Speaker 4: Yeah, I will tell you that. Like, I just feel
Speaker 4: like there are conversations happening in every corner you can
Speaker 4: imagine right now, and I'd like to see those conversations
Speaker 4: be turned into useful and practical pathways forward, like calling
Speaker 4: for governance. If you're a major tech company and saying,
Speaker 4: like these technologies that I'm creating create existential risk for humanity,
Speaker 4: please regulate it. Or if you think that they present
Speaker 4: existential risk for humanity, don't just rush ahead, and you know,
Speaker 4: like come forward with something positive rather than saying my
Speaker 4: job is just to create the technology, your job is
Speaker 4: to govern it. Like that's not the pathway forward either.
Speaker 4: I have questions from listeners who know you're coming on.
Speaker 4: Oh great, yeah, please, But before.
Speaker 3: We do, we'll donate to a relevant cause. And this
Speaker 3: week it's going to Human Rights Watch, which is a
Speaker 3: group of experts, lawyers, and journalists who investigate and report
Speaker 3: on abuses happening in all corners of the world, and
Speaker 3: then they direct their advocacy toward governments, armed groups, and businesses.
Speaker 3: And you can find out more at HRW dot org.
Speaker 3: And we will link that in the show notes and
Speaker 3: thanks to sponsors of the show who make that donation possible.
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Speaker 3: Okay Onto questions written by actual human listeners made of
Speaker 3: meat and water. Let's start with something optimistic. A ton
Speaker 3: of people. Lena Brotsky, Anina Evesy, Chris Blackthorn, Megsie, Alexandra Catoule,
Speaker 3: Adam Silk, Kata mccaffee, Madison Piper, and Will Mack want
Speaker 3: to know. Can we use AI for good? Rye of
Speaker 3: the Tiger wants to know what will AI's role look
Speaker 3: like in the fight against climate change, for example? Or
Speaker 3: should we be using AI for the toils like meal
Speaker 3: planning and trip planning and things like that.
Speaker 4: Yeah, so I think we can absolutely use AI for good.
Speaker 4: And first, I would say a friend of mine, Orly Lobul,
Speaker 4: wrote a book recently called The Equality Machine, and it's
Speaker 4: all about using AI to achieve better equality in society
Speaker 4: and gives kind of example after example of both how
Speaker 4: it could be done and how it is being done
Speaker 4: in some context. I think recognizing that there is this
Speaker 4: terrifying narrative about A but that actually AI is already
Speaker 4: making our lives better in many, many ways, is an
Speaker 4: important thing to look at and that we can put
Speaker 4: it to solving some of the biggest problems in society,
Speaker 4: right from climate change and trying to generate novel ideas
Speaker 4: to testing and identifying and this is already happening novel
Speaker 4: compounds that could be used to solve some of the
Speaker 4: worst diseases, to being used to identify the causes of
Speaker 4: different diseases, to identifying better patterns that help us to
Speaker 4: address everything from neurological disease and suffering to the existential
Speaker 4: threats to humanity like climate change. So I absolutely think
Speaker 4: it can be used for good. It is being used
Speaker 4: for good, it could be used for more good. We
Speaker 4: have to better align the tech companies with the overall
Speaker 4: ways of human flourishing, right. I mean, if you were
Speaker 4: to use AI to improve brain health instead of to
Speaker 4: addict andish brains, that would be phenomenal, and it could
Speaker 4: be used to do that. It can be used for
Speaker 4: mental health treatment and for solving neurological disease and suffering,
Speaker 4: or it can be used to addict people and keep
Speaker 4: them stuck on technology. We need to figure out a
Speaker 4: way to align the incentives of tech companies with these
Speaker 4: ideas of AI for good.
Speaker 3: It'll be so interesting to see if they are getting
Speaker 3: a lot of feedback from our brains. Any mental health
Speaker 3: challenges or speaking as someone who has anxiety and is neurodivergent, Hello, Hi,
Speaker 3: Things like ADHD autism, those have been so overlooked in
Speaker 3: some populations. It would be interesting to see people getting
Speaker 3: a better understanding of their own brains that maybe medicine
Speaker 3: has overlooked because of demographics for a long time.
Speaker 4: You know, Yeah, I have a TED talk that just
Speaker 4: came out that the first half of the TED talk
Speaker 4: actually focuses on all of the positive ways that neurotechnology
Speaker 4: can be used and all of the hope that it offers,
Speaker 4: Like us tracking our everyday brain activity could help us
Speaker 4: better understand what stress this is out. You know, the
Speaker 4: earliest stages of glioblastoma, the worst and most threatening form
Speaker 4: of aggressive brain cancer, is the earliest stages of Parkinson's
Speaker 4: and Alzheimer's disease. Better solutions for ADHD and trauma, you know,
Speaker 4: everything from like understanding the impact of technology on our
Speaker 4: brains to impact the understanding the impact of having that
Speaker 4: glass of wine or that cup of coffee on the
Speaker 4: brain and how it reacts to it. Gaining insight into
Speaker 4: our own brain activity could be the key to unlocking
Speaker 4: much better mental health and well being. And I think
Speaker 4: if it's put in the hands of individuals and used
Speaker 4: to empower them, that will be tremendous and phenomenal. So
Speaker 4: long as we don't overshadow those benefits or outweigh those
Speaker 4: benefits with the dystopian misuses of the technology, which are
Speaker 4: very real and very possible right of using in the
Speaker 4: same way that companies are using all kinds of algorithms
Speaker 4: to predict our purchasing behavior or to nudge us to
Speaker 4: do things like watch the tenth episode in a row
Speaker 4: of a show and rather than breaking free and getting
Speaker 4: some sleep, which is important for brain health. If the
Speaker 4: companies don't use brain data to commodify it to inform
Speaker 4: a more orwellian workplace, get back to it. If governments
Speaker 4: don't use it to try to surveil brains and to
Speaker 4: intrude on freedom of thought, but instead it's used by
Speaker 4: individuals to have greater power over their own health and
Speaker 4: well being in their own brains, it will be tremendous.
Speaker 4: We just have to really worry about those misuses and
Speaker 4: how we safeguard against them.
Speaker 3: So the day before this interview, a TED talk featuring
Speaker 3: Nita went live, and in it she discusses the loss
Speaker 3: of her daughter and the grief that overwhelmed her, and
Speaker 3: she tells of how using biofeedback to understand her own
Speaker 3: sorrow and trauma from the experience helped her so much.
Speaker 3: But how individual's brain data should be protected and this
Speaker 3: wrenching personal story that she tells, plus her long backgrounds
Speaker 3: in ethics and science and philosophy, make her very uniquely
Speaker 3: suited to see this issue from a lot of angles,
Speaker 3: and a lot of patrons had questions about surveillance and
Speaker 3: brain data and even neural hardware, including Katie mccaffee, Ryan Marlowe,
Speaker 3: and Sandy Green, who asked about things like medical devices
Speaker 3: like brain implants being used for surveilling or for commerce.
Speaker 3: I was curious, so were some listeners to PAVCA thirty
Speaker 3: four Aminik David and Alex Htman's words, if we were
Speaker 3: to implant chips into human brains, what would they most
Speaker 3: likely be capable of? Would they be more in the
Speaker 3: realm of modulating real inputs, or would they be capable
Speaker 3: of generating new thoughts? Alex says it seems far fetched,
Speaker 3: but also the truth can be strange to the fiction.
Speaker 3: So is that a really big leap philosophically and legally
Speaker 3: and technologically.
Speaker 4: I think it might be easier to interrupt thoughts than
Speaker 4: to create new thoughts. However, I guess philosophically that is
Speaker 4: creating new thoughts if you're interrupting thoughts right because you're
Speaker 4: letting other thoughts happen. But implanted neurotechnology right now is
Speaker 4: very limited. It's very difficult to get neurotechnology into people's brains,
Speaker 4: and there are forty people who are part of clinical
Speaker 4: trials that have implanted neurotechnology right now. It's a tiny
Speaker 4: number of people. If neuralink, you know, and Elon Musk
Speaker 4: has his way, there will be far more people who
Speaker 4: are part of that. But implanted neurotechnology is limited. What
Speaker 4: it primarily is being used to do is to get
Speaker 4: signals out of the brain, that is, to listen to
Speaker 4: intention to move or to form speech, and to translate
Speaker 4: that in ways that then can be used to operate
Speaker 4: other technology.
Speaker 3: If you're like, what is neuralink again? It sounds like
Speaker 3: a commuter train, but this is actually a side hustle
Speaker 3: of Twitter owner and Tesla guy and tunnel maker Elon
Speaker 3: Musk and he described this cosmetically undetectable, coin sized brain
Speaker 3: accessory as a wireless implanted chip that would enable someone
Speaker 3: who is quadriplegic or tetraplegic to control a computer or mouse,
Speaker 3: or their phone or really any device just by thinking.
Speaker 3: And he likened it to a fitbit in your skull
Speaker 3: with tiny wires that go to your brain. So a
Speaker 3: robot surgeon, also invented by Neuralink, sows sixty four threads
Speaker 3: with over one thousand electrodes into the brain matter, which
Speaker 3: allows the recipient to control devices or robotic arms or
Speaker 3: a screen using telepathic typing, which sounds pretty cool. And
Speaker 3: in early twenty twenty two, it came to light that
Speaker 3: roughly fifteen hundred animals had been killed in the testing
Speaker 3: process since twenty eighteen, some from human errors like incorrect
Speaker 3: placement on pig spines or wrong surgical glue used in
Speaker 3: primate test subjects, and some former employees reported that the
Speaker 3: work there was often rushed and that the vibe was
Speaker 3: just high key stressful. But nevertheless, Neuralink announced just a
Speaker 3: few months ago that they got the green light from
Speaker 3: the FDA to launch their human trials and if you're like, hey,
Speaker 3: I am always losing the TV remote, so wire me up, musk,
Speaker 3: please cool your jets. Because they added that recruitment is
Speaker 3: not yet opened for their first clinical trial. More on
Speaker 3: that as it develops. But I guess when I said
Speaker 3: that we could become bubbles of chimp, that was really
Speaker 3: on the optimistic side of things.
Speaker 4: What is possible, though, and this is one of the
Speaker 4: things I talk about in my TED talk, is it's
Speaker 4: possible to use neurostimulation in the brain. So I describe,
Speaker 4: for example, the case of Sarah, where she had intractable
Speaker 4: depression and through the use of implanted electrodes, was able
Speaker 4: to reset her brain activity.
Speaker 3: This side note was conducted at the University of California
Speaker 3: and Servirascote, where neuroscientists implanted what's called a BCI, or
Speaker 3: brain computer interface, which was initially developed for epilepsy patients,
Speaker 3: into someone with treatment resistant depression, and one surgeon on
Speaker 3: the team said, when we turned this treatment off on
Speaker 3: our patient's depression, symptoms dissolved and in a remarkably small
Speaker 3: time she went into remission and the patient, Sarah, reported
Speaker 3: laughing and having a joyous feeling. Wash over her that
Speaker 3: lasted at least a year after this implantation.
Speaker 4: So this specific pattern of neural activity that was happening
Speaker 4: when she was the most symptomatic was traced using the
Speaker 4: implanted technology, and then, like a pacemaker for the brain,
Speaker 4: those signals were interrupted and reset each time she was
Speaker 4: experiencing them. That doesn't create a new thought. What it
Speaker 4: does is interrupt an existing thought. But philosophically you could
Speaker 4: say that creates a new thought. It creates for her
Speaker 4: an experience of being able to have a more typical
Speaker 4: range of emotions. I think specific thoughts would be very
Speaker 4: hard to encode into the brain. I won't say never.
Speaker 3: So brain hacking and hacking into your brain may radically
Speaker 3: change the way that we think and feel, if we
Speaker 3: don't blow up the planet first, which is not an
Speaker 3: intelligent thing to do. Speaking of intelligence, many patrons wanted
Speaker 3: to know what is in a name. Alexis will Clark Zombot,
Speaker 3: who proposed the term OI or organic intelligence for human
Speaker 3: thinking and history buff Connie Brooks. They all had questions
Speaker 3: about AI and the term AI. Is it intelligent? Is
Speaker 3: it artificial? Are they ever going to do a rebrand
Speaker 3: on that? Does it give people the wrong idea of
Speaker 3: what it is.
Speaker 4: Yeah. So I mean a lot of the technologists out
Speaker 4: there were computer scientists saying this isn't artificial intelligence because
Speaker 4: that assumes that there's intelligence. These aren't intelligent. They are
Speaker 4: task specific algorithms that are designed to do particular things,
Speaker 4: and that if we ever get to the point where
Speaker 4: you start to see more generalized intelligence, then that's the
Speaker 4: point at which it makes more sense to talk about
Speaker 4: artificial intelligence.
Speaker 3: But not everyone is so casual about that assessment.
Speaker 4: Interestingly, Eric Korvitz, who is the chief Science officer at
Speaker 4: Microsoft who has partnered with open Ai for CHATBT, he
Speaker 4: just published his essay on this AI Athology series and
Speaker 4: he talks about how his experience with GPT four was
Speaker 4: to see a lot of threads of intelligence, of what
Speaker 4: we think of as intelligence, and you see increasingly a
Speaker 4: lot of examples of reasoning more like humans. I think
Speaker 4: one of the examples I've seen out there is giving
Speaker 4: GPT four a question of like, okay, you have some
Speaker 4: eggs a laptop, it's like five or six items, how
Speaker 4: would you stack them? And then comes out and explains
Speaker 4: how you would stack them, and like you would put
Speaker 4: the book on the bottom, and then you would put
Speaker 4: a set of eggs that were spread out so that
Speaker 4: they could be stable, and then you would put the
Speaker 4: laptop in a particular configuration and blah blah blah, And
Speaker 4: why that kind of reasoning was more like human intelligence
Speaker 4: than it is like an algorithm. And those are really
Speaker 4: interesting to think about. Like what is intelligence? Is really
Speaker 4: the fundamental question I think when somebody is saying is
Speaker 4: it really artificial intelligence? It is to have a particular
Speaker 4: perspective on what intelligence is and means and then to say, well,
Speaker 4: that isn't intelligence. Or if a generative AI model says
Speaker 4: it's happy, that it can't really be because that's not
Speaker 4: an authentic emotion because it's never experienced the world and
Speaker 4: it doesn't have sensory input and sensory output. Or if
Speaker 4: a generative AI model says, here's what the ratings of
Speaker 4: wine are and what an excellent wine is, it can't
Speaker 4: possibly know because it's never tasted wine, you know, And
Speaker 4: then there's a question of like is that kind of
Speaker 4: intelligence what you need, which is experiential knowledge and not
Speaker 4: just knowledge built on knowledge. There are some forms of intelligence,
Speaker 4: like emotional intelligence, which you might think really requires experiencing
Speaker 4: the world to authentically have that kind of intelligence.
Speaker 3: I don't know shit about wine and sometimes I'm bad
Speaker 3: at my own emotions. Oh well, we can learn. Speaking
Speaker 3: of learning, many patrons who are students had thoughts and
Speaker 3: questions like Handy Dandy, Mister Mandy, Natalie Jones, Josie Chase,
Speaker 3: and Slayer, as well as educators including Nina Brodsky, Julie Vallmer,
Speaker 3: Leah Anderson, Jenna Congden, Theodore Visian Hudson Ansley, and Nina
Speaker 3: eve Z. There were several teachers who wrote in with questions.
Speaker 3: Katie Bauer says, I'm a middle school teacher and I
Speaker 3: just started having students use AI tools to write essays
Speaker 3: for them. Help talk me down. How do we embrace
Speaker 3: new tech but also teach students how to navigate this
Speaker 3: new landscape with solid ethics and an understanding of the
Speaker 3: need to develop skills that don't provolve around AI technology
Speaker 3: and Liz Park first time question asker their teacher and
Speaker 3: they feel that teaching, along with a lot of other jobs,
Speaker 3: just can't be handed off to AI and expected to
Speaker 3: have the same impact because machines, no matter how advanced,
Speaker 3: won't be able to individualize education and provide warmth and
Speaker 3: et cetera.
Speaker 4: Well, you know it's funny because I hear that almost
Speaker 4: the same question in both, Right, what is the role
Speaker 4: of education and human to human education in a world
Speaker 4: of generative AI? And I think that's a great question
Speaker 4: to be asking. And I would say, first, I'm so
Speaker 4: glad that they were giving their students the assignment of
Speaker 4: working with CHATCHYBT and trying to understand it, because I
Speaker 4: think there are skills that you can't learn from generative AI,
Speaker 4: and if you don't learn them, we will not be
Speaker 4: able to interact well with them and use them well.
Speaker 4: And these are critical thinking skills. And if the same
Speaker 4: old assignments are how we're trying to teach students, then yeah,
Speaker 4: students are just going to go to chat GYBT and
Speaker 4: say here's the book, generate a thesis statement for me,
Speaker 4: and write my essay, right, But they will have lost
Speaker 4: out on the ability to generate a thesis statement and
Speaker 4: what that critical thinking skill is, and lost out on
Speaker 4: the ability to build an argument and how you do so,
Speaker 4: lost out on the ability to write and understand what
Speaker 4: good writing is, and they won't be able to interrogate
Speaker 4: the systems well, because they won't have any of the
Speaker 4: skills necessary to be able to tell fact from fiction
Speaker 4: and what is good writing or anything else? So then
Speaker 4: the question is what you do? And it's the teachers
Speaker 4: and higher education and K through twelve education needs to
Speaker 4: be thinking about, Okay, what are the fundamental skills of
Speaker 4: reasoning and critical thinking and empathy and emotional intelligence and
Speaker 4: mental agility that we think are essential and that we
Speaker 4: have been teaching all along, But we've been teaching by
Speaker 4: task that now can be outsourced. And then how do
Speaker 4: we shift our teaching to be able to teach those skills?
Speaker 4: And you know, if you go back to like the
Speaker 4: Socratic dialogues, there's an art to asking the question to
Speaker 4: seeking truth, and there is an art to asking the
Speaker 4: question of generative AI models in seeking the truth or
Speaker 4: and seeking good outputs. And we have to be teaching
Speaker 4: those skills if we want to move ahead.
Speaker 3: I wasn't sure what the Socratic method of questioning was,
Speaker 3: so I asked the literature via computer, and I found
Speaker 3: that it involves a series of focused, yet open questions
Speaker 3: meant to to unravel thoughts as you go. And according
Speaker 3: to one article, Instead of a wise person lecturing, the
Speaker 3: teacher acts as though ignorant of the subject, and one
Speaker 3: quote attributed to Socrates reads, the highest form of human
Speaker 3: excellence is to question oneself and others. So don't trust
Speaker 3: my wine recommendations, but do cut bangs if you want
Speaker 3: text a crush, ask a smart person a not smart question,
Speaker 3: because worms are going to eat us all one day.
Speaker 3: But yeah, the point of education isn't to get a
Speaker 3: good grade, but to develop skills that in the future
Speaker 3: are going to get you out of a jam. So
Speaker 3: many jams.
Speaker 4: And I think your other person talking about that they
Speaker 4: can never replace human empathy, that's right, But don't be
Speaker 4: blind to the fact that they can make very powerful
Speaker 4: personal tutors as well. And they may not be able
Speaker 4: to tell when a student is struggling, or when they
Speaker 4: need emotional support, or when they may be experiencing abuse
Speaker 4: at home and need the support of the school to
Speaker 4: be able to intervene, for example, but they can go
Speaker 4: beyond a teacher can go. A teacher doesn't have the
Speaker 4: capability to sit down with every student for hours and
Speaker 4: help them work through ten different ways of explaining the
Speaker 4: same issue to somebody. And so you help them learn
Speaker 4: how to ask the questions, and then they could spend
Speaker 4: all night long say Okay, well I didn't understand that explanation.
Speaker 4: Can you try explaining it to me a different way?
Speaker 4: Can you try explaining it to me as if you
Speaker 4: were telling my grandmother, I don't understand what that word means.
Speaker 4: There's no teacher on earth who has either the patience
Speaker 4: for that or the time or is paid well enough
Speaker 4: to do that for every student, and so I think
Speaker 4: it can be an extraordinary equalizer. You know, right now,
Speaker 4: like wealthier parents are able to give private tutors to
Speaker 4: their kids, Okay, now you can have a generative AI
Speaker 4: model serve as a private tutor that can be customized
Speaker 4: every student based on how they learn. That doesn't mean
Speaker 4: we don't need teachers to be able to be empathetic
Speaker 4: and to help students learn how to engage with the
Speaker 4: mom models and learn critical thinking skills, or to create
Speaker 4: a social environment to help develop their emotional intelligence and
Speaker 4: their digital intelligence. But it does mean that there is
Speaker 4: this additional tool that could actually be incredibly beneficial and
Speaker 4: can augment how we're teaching.
Speaker 3: Okay, but outside the classroom and into your screens folks
Speaker 3: had questions, including Michael Hiker, Kevin Glover, Andrea Devlin, Genna Congden, Grandit,
Speaker 3: State of Mind, Chris Blackthorne, R. J. Deutge, and one
Speaker 3: big question a lot of listeners had is Rebecca new
Speaker 3: Part says, what's your favorite or least favorite portrayal of
Speaker 3: AI and media? Chris Whitman wants to know what is
Speaker 3: your favorite AI storyline based movie and why is it?
Speaker 3: Ex Machina? Someone else said Missus Davis? Should we turn
Speaker 3: off Missus Davis? If we could? How do we prevent
Speaker 3: Terminator two? Whether or not you watch Black Mirror, anything
Speaker 3: that you feel like pop culturally written by humans that
Speaker 3: you've loved or hated.
Speaker 4: I love Minority Report. It's an oldie but goody, but
Speaker 4: it really informs a lot of my work, and I
Speaker 4: think it's great.
Speaker 1: I'm placing you under arrest with future Murder of Sarah Marx,
Speaker 1: you to manent the.
Speaker 2: Future can be seen.
Speaker 4: I think that some of the modern shows that I like,
Speaker 4: like Severance, Altered Carbon I thought was a great series,
Speaker 4: Black Mirror, Yes, you know, all of those I think
Speaker 4: are terrific and creepy. I appreciate those stories and really
Speaker 4: raising consciousness about some of the existential threats. But I
Speaker 4: would like to see stories that give us some more
Speaker 4: balanced perspective. Sometimes I guess that doesn't make for good film,
Speaker 4: But you know, look the fears of like we don't
Speaker 4: fully understand consciousness, let alone how emergent properties of the
Speaker 4: human brain happen, let alone how emergent properties could happen
Speaker 4: an incredibly intelligent system that we are creating. I share
Speaker 4: those fears, like I don't know where all of this
Speaker 4: is going, and I worry about it, and I don't
Speaker 4: think anybody has an answer about how to safeguard against
Speaker 4: those existential threats, And we should be doing things to
Speaker 4: try to identify them and to identify the points and
Speaker 4: identify what the solutions would be if we actually start
Speaker 4: to see those emergent properties, and those emergent properties are threatening,
Speaker 4: Like we need monitoring systems, we also, in the meantime
Speaker 4: need to be looking at the good and figuring out
Speaker 4: how to better distribute the good, how to better educate people,
Speaker 4: how to change our education systems to catch up with it,
Speaker 4: how to recognize that the right answer for the writer's
Speaker 4: strike isn't to outsource its to chat GBT and there's
Speaker 4: something uniquely human about the writing of stories and the
Speaker 4: sharing of stories and the creation of art, and that
Speaker 4: that's part of the beauty of what it means to
Speaker 4: be human. And so those conversations about the role in
Speaker 4: our lives and how to put it to uses that
Speaker 4: are good and still preserve human flourishing. Like that, I
Speaker 4: feel like is what we need to be doing in
Speaker 4: the meantime, right before it actually tortures us.
Speaker 3: All that is great advice. And the last questions I
Speaker 3: always ask is always like, what's the worst part about
Speaker 3: your job? A lot of people say might be jetlag, meetings, emails,
Speaker 3: But I will outsource that to the patrons who wanted
Speaker 3: to know are we fucked? So we wanted to know
Speaker 3: are we fucked?
Speaker 6: So?
Speaker 3: What is the most fucked thing about what you do
Speaker 3: or learn?
Speaker 6: So?
Speaker 4: I mean, we're fucked if we let ourselves be, and
Speaker 4: I fear that we will, right, I mean, so I
Speaker 4: can tell people until I turned blue in the face
Speaker 4: about the potential promise of AI and certainly the promise
Speaker 4: of neurotechnology if we put it to good use, and
Speaker 4: if we safeguard against the Orwellian misuses of it in society.
Speaker 4: But like we seem to always go there. We seem
Speaker 4: to always like go to the Orwellian and do the
Speaker 4: worst thing and put it to the worst applications and
Speaker 4: be driven just by profit and not by human flourishing.
Speaker 4: And so if we keep doing that, then yeah, we're
Speaker 4: kind of fucked. And if we actually like heed the
Speaker 4: wake up call and do something about it, like put
Speaker 4: into place not only a human right to cognitive liberty,
Speaker 4: but also the systems, the governance, the practices, the technologies
Speaker 4: that help cultivated in society. I mean, if we invest
Speaker 4: in that, we have a bright and happy future ahead.
Speaker 4: If we don't, you know, it's not good.
Speaker 3: What about to be such a globally recognized, trusted voice
Speaker 3: on this. Obviously, I was so pumped to interview you,
Speaker 3: Like I came straight out of the gate being like,
Speaker 3: I'm terrified I'm talking to you. What is it about
Speaker 3: your work that gets you excited? What kind of keeps
Speaker 3: you motivated?
Speaker 4: I guess I'm also fascinated and terrified, right, I mean,
Speaker 4: so like it's almost like the horror show where you
Speaker 4: can't look away, And so I'm just motivated to continue
Speaker 4: to look and to learn and to research and then
Speaker 4: I guess at the end of the day, I am
Speaker 4: an eternal optimist. Like I just I believe in humanity.
Speaker 4: I believe we can actually find a pathway forward, and
Speaker 4: that if I just try hard enough, right, if I
Speaker 4: just like get the message out there and work with
Speaker 4: enough other incredibly thoughtful people who care about humanity, that
Speaker 4: we will find a good pathway forward. So I'm driven
Speaker 4: by the hope and the fascination. I'm driven to continuously
Speaker 4: learn more, and I'm just grateful that people seem to respond.
Speaker 4: I'm encouraged that in this moment, people seem to really
Speaker 4: get it. They really seem to be interested in working
Speaker 4: together collectively to find a better pathway forward.
Speaker 3: I feel like you walking into a rum or a
Speaker 3: conversation is like have you ever seen a piece of
Speaker 3: chicken thrown into piranhas? All of us are just like
Speaker 3: the rest of us are like intellectual piranhas, being like,
Speaker 3: please don't be everything you don't. I'm gonna huggle You're
Speaker 3: out of thank you.
Speaker 4: Well, that's the good thing is I can have hugs too, right,
Speaker 4: And so I'm also a mom. At the end of
Speaker 4: the day, I have two wonderful little girls at home
Speaker 4: who keep me grounded and see the world full of
Speaker 4: curiosity and kind of brilliance, of all kinds of possibility.
Speaker 4: And I want to help them continue to see the
Speaker 4: world as this kind of magical place. I want it
Speaker 4: to still be that place for them as they grow up.
Speaker 3: So ask actual intelligent people some analog questions, because the
Speaker 3: one thing that we can agree on is that there
Speaker 3: is some power in learning, whether you're a person or
Speaker 3: a machine. And now that you know some basics, you
Speaker 3: can keep up with some of the headlines, but honestly,
Speaker 3: take news breaks, go outside, smell a tree, play pickleball
Speaker 3: or something, or go read Nita's book. It's called The
Speaker 3: Battle for Your Brain, Defending the right to think freely
Speaker 3: in the Age of Neurotechnology. Will link that and her
Speaker 3: social media handles in the show notes, as well as
Speaker 3: so much more on our website at aliward dot com
Speaker 3: slash ologies slash neurotechnology well also smologies are kid friendly
Speaker 3: and Shure episodes. Those are up at aliward dot com
Speaker 3: slash Smologies linked to the show notes. Thank you, Zeegredriguez,
Speaker 3: Thomas and Shared Sleeper of Mindsham Media, and Mercedes Maitland
Speaker 3: of Maitland Audio for working on those. We are at
Speaker 3: ologies on Instagram and Twitter, and I'm Ali Ward on
Speaker 3: both Just one L and Ali. Thank you patrons at
Speaker 3: patroon dot com for such great questions. You can join
Speaker 3: for a dollar a month if you like. Ologies Merch
Speaker 3: is for sale at reasonable prices at ologiesmerch dot com.
Speaker 3: Thank you Susan Hale for handling that among all of
Speaker 3: her many responsibilities as managing producer. Noel Dilworth schedules for us.
Speaker 3: Aaron Talbert admin Zoologies podcast Facebook group with this syst
Speaker 3: from Bonnie Dutch and Shannon feltis also Happy birthday to
Speaker 3: my sister Celeste, who has a great brain. Emily White
Speaker 3: of the wordery xr professional transcripts and those are at
Speaker 3: alliwar dot com, slash Ologies Dash extras for free. Kelly R.
Speaker 3: Dwyer does our website. She can do yours too. Mark
Speaker 3: David Christiansen assistant edited this and lead editor and alarmingly
Speaker 3: smart Mercedes Maitland of Maitland Audio pulls it all together
Speaker 3: for us each week. Nick Thorpe wrote and performed the
Speaker 3: theme music. And if you stick around until the end
Speaker 3: of the episode, I tell you a secret and I'm
Speaker 3: going to treat this space like a confessional booth if
Speaker 3: you don't mind. Okay, So once I ran into this
Speaker 3: guy that I had dated who had dumped me, and
Speaker 3: he was with his lovely new girlfriend, and I pretended
Speaker 3: like I didn't hear his new girlfriend's name, right, I
Speaker 3: was like, what is it is? If I hadn't been
Speaker 3: six years deep in her Facebook like the day they
Speaker 3: became official. And I still feel guilty about that. But
Speaker 3: I'm telling you that because computers, Wow, they've changed our lives.
Speaker 3: And also humans were so goofy and flawed. But you know,
Speaker 3: everyone's code has bugs, and we just keep upgrading our
Speaker 3: software until things work well enough. Okay, go enjoy the
Speaker 3: outdoors if you can.
Speaker 5: For bye, pacadermatology, homeology, crypto, zoology, lithologyechology, meteorology, factology, anthology, seriologyology.
Speaker 5: I am now telling the computer exactly what you can
Speaker 5: do with a lifetime supply of chocolate.
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Speaker 2: the tain nudovshude will kill Nagatarhu la
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Speaker 3: augustnyavri anda arvad is fugum more tey rig h i
Speaker 3: a punk iye is colloculala a on tudoros urgras Lonza
Speaker 3: if we wield a naheren